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Damage detection of bridge structures during their operating lifetime is essential. In this paper, two approaches, All Degrees of Freedom and Reduction of the Degrees of Freedom methods, are used to detect the damages in structures. The first method considers All Degrees of Freedom of the structure and the second method, Reduction of the Degrees of...
Contexts in source publication
Context 1
... planar steel truss presented in Gomes & Silva (2008), as shown in Figure 1, is used. The total number of elements in this truss is 15. ...
Context 2
... the first 7 modes, both methods are compared to considering 3%-noise. The results of the MSEBI values with noise effects in three damage cases for the first 7 modes are shown in Figure 10. As 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 ...
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In this paper, a new method proposed for structural damage detection from limited number of sensors using extreme learning machine (ELM). One of the main challenges in structural damage identification problems is the limitation in the number of used sensors. To address this issue, an effective model reduction method has been proposed. To condense m...
Citations
... Lale Arefi and Gholizad (2020) used the modal strain energy method with the System Equivalent Reduction Expansion Process method in truss structures. The results showed the presented method is effective for detecting the damage in truss structures [34]. ...
The subject of structural health monitoring and damage
identification of structures at the earliest possible stage has
been a noteworthy topic for researchers in the last years.
Modal strain energy (MSE) based index is one of the
efficient methods which are commonly used for detecting
damage in structures. It is also more effective and
economical to employ some methods for reducing the
degrees of freedom in large-scale structures having a large
number of degrees of freedom. The purpose of this study is
to identify structural damage via an index based on MSE and
reconstructed mode shapes. The Guyan reduction method
(GRM) is utilized here to reconstruct the mode shapes.
Therefore, in the first step by employing GRM, mode shapes in
slave degrees of freedom are estimated by those of master
degrees of freedom. In the second step, the modal strain energy
based index (MSEBI) is used to find the location of damaged
elements. In order to assess the efficiency of the method, two
standard examples are considered. Damage is identified with
considering complete mode shapes and reconstructed mode
shapes, and the results are compared together. The outcomes
show that the combination of MSE and GRM can be useful
for the structural damage detection, when considering the
noise.
... Lale Arefi and Gholizad (2020) used the modal strain energy method with the System Equivalent Reduction Expansion Process method in truss structures. The results showed the presented method is effective for detecting the damage in truss structures [34]. ...
The subject of structural health monitoring and damage
identification of structures at the earliest possible stage has
been a noteworthy topic for researchers in the last years.
Modal strain energy (MSE) based index is one of the
efficient methods which are commonly used for detecting
damage in structures. It is also more effective and
economical to employ some methods for reducing the
degrees of freedom in large-scale structures having a large
number of degrees of freedom. The purpose of this study is
to identify structural damage via an index based on MSE and
reconstructed mode shapes. The Guyan reduction method
(GRM) is utilized here to reconstruct the mode shapes.
Therefore, in the first step by employing GRM, mode shapes in
slave degrees of freedom are estimated by those of master
degrees of freedom. In the second step, the modal strain energy
based index (MSEBI) is used to find the location of damaged
elements. In order to assess the efficiency of the method, two
standard examples are considered. Damage is identified with
considering complete mode shapes and reconstructed mode
shapes, and the results are compared together. The outcomes
show that the combination of MSE and GRM can be useful
for the structural damage detection, when considering the
noise.
This paper presents a novel statistical analysis-based approach to non-parametric damage detection in truss bridges. The method utilizes the normalized acceleration response time histories (NARTHs) of a bridge under random excitation. The coefficients of variation matrices are calculated using NARTHs for the truss bridge in both its baseline and damaged states. The results are shown as the difference in covariance matrices (DCMs) between the two conditions (pristine and damaged). The row or column-wise summation of the DCM matrix yields a summation of the difference in covariance matrix (SDCM) bar plot having one distinct peak for the damaged member. The location and relative severity of the damage can be determined by examining the DCM matrix and the SDCM bar plot. The variation in magnitude of the coefficients demonstrates the relative severity of damage. Experimental investigation of the proposed method for detecting damage on the truss bridge shows promising results. The approach is then numerically validated using a finite element model of a truss bridge. The proposed method effectively identified, located, and evaluated damage, even when the acceleration time histories are contaminated with noise. The case of multiple-member damage detection in the truss structure is further investigated in the study. The early detection of damage and monitoring of its progression through this method can assist in creating efficient maintenance strategies for truss bridge infrastructure.
In this work, we propose a numerical strategy to detect damages in truss and beam structures exploiting lowest frequencies and mode shapes that are employed to calculate the flexibility matrix. In particular, for truss structures, the modal strain difference between damaged and healthy structures is used to identify the element characterized by the highest value of strain change, which corresponds to the most likely damaged element in the structure. Conversely, for beam structures, the highest value of modal curvature change is used as an index of element damage. Both procedures are validated using pseudo-experimental data accounting for noise pollution in mode shapes components.KeywordsDamage detectionFlexibility matrixModal curvatureModal strain
Damage detection of structures is one of the most important topics in structural health monitoring. In practice, the response is not available at all structural degrees of freedom, and due to the installation of sensors at some degrees of freedom, responses exist only in limited number of degrees of freedom. This paper is investigated the damage detection of structures by applying two approaches, AllDOF and Dynamic Condensation Method (DCM), based on the Modified Modal Strain Energy Method (MMSEBI). In the AllDOF method, mode shapes in all degrees of freedom is available, but in the DCM the mode shapes only in some degrees of freedom are available. Therefore by methods like the DCM, mode shapes are obtained in slave degrees of freedom. So, in the first step, the responses at slave degrees of freedom extracted using the responses at master degrees of freedom. Then, using the reconstructed mode shape and obtaining the modified modal strain energy, the damages are detected. Two standard examples are used in different damage cases to evaluate the accuracy of the mentioned method. The results showed the capability of the DCM is acceptable for low mode shapes to detect the damage in structures. By increasing the number of modes, the AllDOF method identifies the locations of the damage more accurately.
